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https://ptsldigital.ukm.my/jspui/handle/123456789/579105| Title: | Hybrid genetic algorithm in the hopfield network for logic satisfiability problem |
| Authors: | Mohd Shareduwan Mohd Kasihmuddin Mohd Asyraf Mansor (USM) Saratha Sathasivam (USM) |
| Keywords: | Genetic Algorithm Exhaustive Search Hopfield network Satisfiability Logic Programming HORN-SAT 3-SAT 2-SAT |
| Issue Date: | Jan-2017 |
| Description: | In this study, a hybrid approach that employs Hopfield neural network and a genetic algorithm in doing k-SAT problems was proposed. The Hopfield neural network was used to minimise logical inconsistency in interpreting logic clauses or programme. Hybrid optimisation made use of the global convergence advantage of the genetic algorithm to deal with learning complexity in the Hopfield network. The simulation incorporated with genetic algorithm and exhaustive search method with different k-Satisfiability (k-SAT) problems, namely, the Horn-Satisfiability (HORN-SAT), 2-Satisfiability (2-SAT) and 3-Satisfiability (3-SAT) will be developed by using Microsoft Visual C++ 2010 Express Software. The performance of both searching techniques was evaluated based on global minima ratio, hamming distance and computation time. Simulated results suggested that the genetic algorithm outperformed exhaustive search in doing k-SAT logic programming in the Hopfield network |
| News Source: | Pertanika Journals |
| ISSN: | 0128-7680 |
| Volume: | 25 |
| Pages: | 139-152 |
| Publisher: | Universiti Putra Malaysia Press |
| Appears in Collections: | Journal Content Pages/ Kandungan Halaman Jurnal |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_116457+Source01+Source010.PDF | 1.12 MB | Adobe PDF |  View/Open |
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